The present invention relates generally to agricultural machinery, especially self-propelled harvesting machines and, more particularly to a system for setting operating parameters of a harvesting machine.
A harvesting machine, such as a combine harvester, is very complex and comprises a large number of machine components with corresponding parameters, which are set by the machine operator. For example, in a combine harvester these machine parameters may include the threshing drum speed, the blower speed, the screen meshes of lower and upper screens, the reel speed, the traveling speed, etc.
The operator of the harvesting machine must set the parameters of the machine components correctly in order to optimally carry out the harvesting operation. There are several different target standards for an optimum harvesting application. For example, one target standard for the harvesting application relates to minimizing losses to the greatest extent possible. On the other hand, in view of the significant time constraints during the short harvesting period, another target standard is to achieve a high throughput or high surface area capacity and thereby harvesting in as short a time as possible. However, the individual target standards are not independent of one another. Thus, for example, there is a correlation between the throughput and the loss. With increasing throughput, there is generally a concurrent increase in loss. Thus the target standard usually is dictated by a compromise between low losses and rapid completion of the harvesting application.
An added difficulty for the machine operator in setting a self-propelled harvesting machine is that, from one harvesting application to the next, there are in each case different external harvesting conditions which require different settings of the parameters of the machine components. For example, it is possible to harvest different crops (wheat, rye, oats, maize, etc.), which may require different operating parameters of the harvesting machine. Other examples of external harvesting conditions are the ripeness of the crop, the grain moisture, the proportion of straw, the straw moisture, the grain size, stand density (yield), etc.
Experienced machine operators who know the effect of external harvesting conditions on the setting of the machine parameters usually succeed in determining the optimal machine settings. For inexperienced operators, however, it is relatively difficult to set the many machine parameters optimally. Even experienced machine operators have problems in setting the harvesting machine optimally at the beginning of the harvesting season.
A system for setting a harvesting machine is proposed in European Patent Application 0 586 99 A2, which is based on a neuronal network. There the external harvesting conditions are detected by sensors and fed to the input neurons of the input layer as signals. The neuronal network serves its concealed layers for information processing and is designed both as a general model of the harvesting machine and as a local model of the machine with respect to individual machine components. The neurons of the output layer in this system then generate the signals for the machine parameters. The realization of such a system for automatically setting a self-propelled harvesting machine based on a neuronal network however requires a very large computing capacity and fast processors. Moreover high expenditure on programming is necessary. These reasons as well as other associated relatively high costs have precluded implementation of a neuronal network in harvesting machines.
It is therefore the object of the invention to provide a relatively inexpensive system which is easy to implement and which allows optimum setting of a self-propelled harvesting machine.